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Updated: Jul 20, 2026
Q & A: 103 Questions and Answers
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| Section | Weight | Objectives |
|---|---|---|
| Data Governance and MLOps | 15% | - Governance and Operations
|
| Data Preparation and Feature Engineering | 20% | - Feature Engineering Techniques
|
| Data Engineering Pipeline Optimization | 25% | - Pipeline Design and Performance
|
| Deployment and Operationalization | 15% | - Model Deployment
|
| Machine Learning Model Optimization | 25% | - Model Tuning and Evaluation
|
1. Which of the following are components of the Apache Spark Streaming architecture? (Select all that apply)
A) Worker node
B) Kafka topics
C) HDFS storage
D) Driver node
E) Discretized streams (DStreams)
2. A manufacturing organization intents to minimize production costs by analyzing real-time data after implementing IoT tools.
Which business driver would be affected if the organization follows this strategy?
A) Operational efficiency
B) Product choices
C) Customer experience
D) New sources of revenue
3. An organization plans to establish a data governance process for a data lake.
What is the correct sequence of steps required to implement the process?
A) 1. Develop the business value statement and a baseline for ongoing measurement of the data governance deployment
2. Define the roles and responsibilities of actors within the data governance process
3. Operationalize the data governance process and assist the deployment team
4. Understand the current and future states of data governance and identify remaining gaps
B) 1. Define the roles and responsibilities of actors within the data governance process
2. Develop the business value statement and a baseline for ongoing measurement of the data governance deployment
3. Operationalize the data governance process and assist the deployment team
4. Understand the current and future states of data governance and identify remaining gaps
C) 1. Define the roles and responsibilities of actors within the data governance process
2. Operationalize the data governance process and assist the deployment team
3. Develop the business value statement and a baseline for ongoing measurement of the data governance deployment
4. Understand the current and future states of data governance and identify remaining gaps
D) 1. Define the roles and responsibilities of actors within the data governance process
2. Operationalize the data governance process and assist the deployment team
3. Understand the current and future states of data governance and identify remaining gaps
4. Develop the business value statement and a baseline for ongoing measurement of the data governance deployment
4. Which of the following are data ingestion tools commonly used in the Hadoop ecosystem? (Select all that apply)
A) Apache Sqoop
B) Apache Flink
C) Apache Beam
D) Apache Kafka
E) Apache Flume
5. Which skill is crucial for a data engineer to effectively manage and optimize large-scale data processing systems?
A) Graphic design
B) Cloud computing
C) Front-end development
D) Data analysis
Solutions:
| Question # 1 Answer: A,D,E | Question # 2 Answer: A | Question # 3 Answer: D | Question # 4 Answer: A,D,E | Question # 5 Answer: B |
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